Table of Contents
Journal of Computational Medicine
Volume 2013, Article ID 513537, 8 pages
http://dx.doi.org/10.1155/2013/513537
Research Article

LASSO-ing Potential Nuclear Receptor Agonists and Antagonists: A New Computational Method for Database Screening

1Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC 27526, USA
2National Exposure Research Laboratory, US-Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, NC 27711, USA
3SimBioSys, Inc., 135 Queen's Plate Drive, Suite 520, Toronto, ON, Canada M9W 6V1
4Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC 27587, USA

Received 1 February 2013; Accepted 28 May 2013

Academic Editor: Gabriela Mustata Wilson

Copyright © 2013 Sean Ekins et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Sean Ekins, “Progress in computational toxicology,” Journal of Pharmacological and Toxicological Methods, 2013. View at Publisher · View at Google Scholar
  • Nathalie Lagarde, Solenne Delahaye, Jean-François Zagury, and Matthieu Montes, “Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores,” Journal of Cheminformatics, vol. 8, no. 1, 2016. View at Publisher · View at Google Scholar